Do you think that AI will ever feel emotions?

I think this was the line by billvon that started this:
Figure out the most efficient trajectories. Learn to fly airplanes better. Understand language. Correct grammar. Predict weather. Paint pictures. Write stories. When installed in a robot, figure out how to walk and run.

What are the Artificial Neural Nets doing in each of these tasks besides, Pattern Matching within the dedicated Task Algorithm? It takes a lot of other kinds of Software to accomplish these tasks. More than what can be accomplished with just an ANN.

 

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Again: says you. Without anything to back it up.

You are using your own beliefs of what AI can and can't do to try to support an argument about what AI can and can't do.

 

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Not true. Google deep learning, for example. You're about 15 years behind the times.

 

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As an Engineer, I work on AI projects from time to time, and I can say with 100% certainty that you are trying to stuff capability into Neural Nets beyond what they are really doing.

 

I was very disappointed when I studied up on Deep Learning a bunch of years ago. Nothing new just extra layers in the Net. It provided better Pattern Recognition and faster configuration times. No Magic new Category of capability from previous Neural Nets. Deep Learning is Marketing Hype for AI Software companies that want to sell products.

 

Within 10 minutes of its birth, a baby fawn is able to stand. Within seven hours, it is able to walk. Between those two milestones, it engages in a highly adorable, highly frenetic flailing of limbs to figure it all out.

• Learning problem.
• 1. Gradient descent.
• 2. Newton method.
• 3. Conjugate gradient.
• 4. Quasi-Newton method.
• 5. Levenberg-Marquardt algorithm.
• Performance comparison.
• Conclusions.

Learning problem

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https://www.neuraldesigner.com/blog/5_algorithms_to_train_a_neural_network#:

A Detailed Guide to 7 Loss Functions for Machine Learning Algorithms with Python Code

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https://www.analyticsvidhya.com/blo...-loss-functions-machine-learning-python-code/

Neural Network Machine Learning Algorithms

Perceptron

https://www.educba.com/neural-network-machine-learning/

 

Well there's your problem. Your 15 year old knowledge is no longer valid.

 

It's all ways of configuring the Neural Net. When the Net is configured it's all Pattern Matching. The Perceptron was conceived back in the 50s. Your information is 70 years old.

 

Could be random, but after watching actual random patterns for a long time, it will be quite apparent that something is going on if the patterns start consistently organizing like this.

 

Where did the 15 years come from?

 

So, is the concept useless or has it been refined? Seems to me most scientific theories have stood the test of time.

 

That's about the time that deep learning started to become a serious field of research.

 

This is new.

MuZero

https://en.wikipedia.org/wiki/MuZero

 

It was hiding in the basement of Academia 10 years before I came onboard. I started looking into it when I started hearing the Marketing Adds for AI promoting Deep Learning. Seems like the Marketing adds finally hit my Consciousness about 5 years ago.

 

Of course it was refined. But a Neural Net or Perceptron or whatever you call it, is still a Pattern Matching tool.

 

Scientists realized that Games were very Algorithmic and Pattern Driven many years ago. Self configuring Neural Nets are not difficult to program, and this has been done for many years. I think the Company in your link has a good product and a good Marketing strategy.

 

And what is the difference? Brains are not pattern matching processors? I told you to watch Anil Seth.

And you believed these people were not seriously trying to create a functional product?
AI is the future, my friend. We better get on board with that.

 

You are comparing Brain Neural Nets with Artificial Neural Nets. Both do Pattern Matching but the Brain does much more. You are comparing Apples with Bowling Balls again.

 

What do you think a brain is ?
As Descartes proved, if you place a brain in a vat attached to a computer and play an outdoor scene, the brain will think it is outdoors walking in the sun. Yes it will imagine more than just experiencing outdoors, but it'll still be in the vat.

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Now suppose you do this with an AI and in addition to an image of the sun you also feed in warmth. Will the AI's thermometer sense the warmth and seeing the sun, imagine a sunlit scene from memory?